Generative artificial intelligence is growing in both consumer and business use cases. generative artificial intelligence is in the business.
- Quickly automating and simplifying project workflows.
- Taking repetitive tasks off the plates of busy employees.
- Helping businesses maintain high quality and volume production standards.
Learn how generative artificial intelligence can be used to improve enterprise use cases.
Generative artificial intelligence landscape is current and future trends.
There are over 100 top artificial intelligence companies.
Generative AI in the Enterprise: Table of Contents
Generative AI Enterprise Use Cases
Some enterprises, like marketing and sales-driven companies, have quickly added generative artificial intelligence into their content creation processes.
Most firms aren't able to produce or support artificial intelligence without external support and more enterprise companies are looking to today's top artificial intelligence companies for assistance
generative artificial intelligence is being integrated into enterprises across industries and departments.
Code generation, documentation, and QA
Writing, completing, and vetting sets of software code are some of the uses of generative artificial intelligence. Quality assurance is the most important emerging use case in this area, with generative artificial intelligence models handling various types of documentation.
Product and app development
Generative artificial intelligence is being used to write product documentation for apps. App development is the most common type of product development for generative artificial intelligence today.
Blog and social media content writing
Large language models are able to create appropriate and creative content with the right inputs and prompt.
A lot of these models allow users to give instructions on article tone and voice, input past written content from the brand, and add other specifications so content is written in a way that sounds human and relevant to the brand's audience.
Inbound and outbound marketing communication workflows
Email and chat threads are often sent to prospective and current customers on a daily basis. The process of moving these people to the next stage of the customer life cycle can be done with the help ofrative artificial intelligence solutions.
Graphic design and video marketing
Graphics, animation, and audio can be generated usingrative artificial intelligence, which can be used for video marketing. If you want to create a marketing video without actors, video equipment, or video editing expertise, you can use voice synthesis and artificial intelligence.
Entertainment media generation
This type of technology is being used to create the graphics for movies and video games, the audio for music and podcasts generation, and the characters for virtual stories.
Creatives are pushing back on the idea that generative artificial intelligence will be the majority of future film content.
Performance management
Business and employee coaching scenarios are included inrative artificial intelligence use cases. When combined with sentiment analysis, contact center call documentation and summarization give managers the information they need to assess current customer service performance and coach employees on ways to improve.
Business performance reporting
generative artificial intelligence can work through a lot of text and data to quickly summarize the main points of a report. It's useful for data that requires more processing before it can be analyzed.
Customer support and customer experience
Customer service questions can be answered by virtual assistants at all hours of the day and night. A human customer support representative is needed to give comprehensive and more human answers without the help of a bot.
Optimized enterprise search and knowledge base
Internal and external searches benefit from the use of artificial intelligence. generative artificial intelligence models can be used to find and summarize enterprise resources when users are searching for information about their job.
generative artificial intelligence models can be used to find answers to brand questions on company websites and other customer facing properties.
Pharmaceutical drug discovery and design
Drug discovery and design processes are being made more efficient with the use ofrative artificial intelligence. Drug discovery using artificial intelligence is one of the areas that is getting the most funding right now, so expect this particular enterprise use case to grow in the coming months and years.
Medical diagnostics
There is still a lot of work to be done inrative artificial intelligence in medicine. Medical professionals can get a better look at certain parts of the human body with the help of image generation and editing tools. Basic diagnostics can be performed on their own by some tools.
There is more aboutrative artificial intelligence in healthcare.
Inverse design
In medicine, manufacturing, and other materials-based industries, generative artificial intelligence is being used to create designs. inverse design uses artificial intelligence to find missing materials in a process and create new materials that meet the requirements.
Consumer-friendly data analysis
generative artificial intelligence can be used to heighten data and consumer privacy.
Artificial intelligence can be used to create synthetic data copies of sensitive data, allowing analysts to analyze and derive insights from the copies without compromising data privacy or compliance.
Smart manufacturing and predictive maintenance
Modern manufacturing usesrative artificial intelligence to help workers create more innovative designs and meet other production goals.
generative models can help simplify the process of assessing complex data from sensors and other parts of the assembly line.
Inventory and supply chain management
There are several components of supply chain management that can be improved. Routes, demand forecasting, supplier risk management, and inventory management can all be made smarter and more accurate with the help of artificial intelligence.
Fraud detection and risk management
This type of technology can quickly analyze large amounts of data and identify anomalies. Fraud detection and risk management can be done with generative artificial intelligence.
You can learn about other generativeAI examples.
How Enterprises Are Using Generative AI Today
There are a number ofrative artificial intelligence enterprise use cases. Some are sticking with subscription-based models, while others are building their own models and versions into their tool stack.
There are a few examples of how major enterprises are using generative artificial intelligence.
Professional services and business operations: Accenture uses case
generative artificial intelligence is being used by a major consulting firm to help its clients.
Banking, sales, customer service, legal, and other industries are just some of the industries that use the generative artificial intelligence services of Accenture.
Life sciences: Nvidia uses case
The Bio NeMo Drug Discovery Cloud Service uses large language modeling to advance and speed up drug discovery.
Travel and hospitality: Expedia uses case
Users can ask questions and get recommendations on travel, lodging, and activities with the help of a travel planning tool. Users can easily book recommended lodging through the intelligent shopping feature.
E-commerce and retail: Shopify uses case
Artificial intelligence can be used to generate product descriptions and other product related content.
Fintech and software development: Stripe uses case
Openai's GPT-4 is being used by Stripe to power better documentation, summarization, and query management for developers that use Stripe Docs
The top 12 leaders ofrative artificial intelligence companies.
Generative AI Use Cases: Ethics and Compliance
There are a lot of unknowns aboutrative artificial intelligence. Most users don't know what data goes into their training
These models have a wide range of capabilities that can help and hurt. generative artificial intelligence models are threatening the careers of many skilled workers.
What can enterprises do to make sure they are complying with security and privacy regulations? There are a few tips to get started with responsible use.
- Only input depersonalized and nonsensitive data into large language models. Otherwise, your most sensitive data could become part of the tool’s training dataset and become exposed to third-party users and companies.
- Stay current with generative AI news and trends. The generative AI space is changing daily, and with that change comes news of companies that are getting the technology right. Yet some companies are taking dangerous and/or unethical steps in their AI development. Staying updated on all of these changes will ensure you only use the most credible tools and work with the most ethical AI providers.
- Create an AI usage and ethics policy for your business. There are policy templates that are publicly available that should cover how internal users in your organization are allowed to use AI tools and also how your business is allowed to invest in third-party tools.
- Offer career training to all employees. Employees are rightfully afraid that parts of their job will soon be outsourced to AI; to combat this fear and build up their career prospects, offer training and certifications that will help them to use AI in their jobs and build skills that cannot easily be demonstrated by AI models.
There are advantages and challenges torative artificial intelligence.
The enterprise use cases for generative artificial intelligence are evolving just as quickly as the capabilities change. New opportunities exist for enterprises to improve their current operations.
generative artificial intelligence is being used to discover new pharmaceuticals and write marketing copy. The key is to consider what model works best for your business, what you're trying to achieve, and how this new business factor will affect your employees and your customers
There are 9rative artificial intelligence applications and tools.
